RS-ESRGAN: Super-Resolution of Sentinel-2 Imagery Using Generative Adversarial Networks

See our project website here.

We used BasicSR codes, which can be found here, and modified it to suit our purposes to work with remote-sensing data.

License

This code cannot be used for commercial purposes. Please contact the authors if interested in licensing this software.

Data

To train with WorldView-2 European Cities dataset, you must download the data and follow the directions in options/train folder.

To work with WorldView-Sentinel pairs, please contact the authors.

Training

• Train the model for Super-resolution with European-cities Dataset python train_esrgan_EUCities.py -opt ./option/train/train_ESRGAN_ESRGAN_WV_5x_v1.json . Checkpoints and logs will be saved as defined in the json file.

Contact

For questions and suggestions use the issues section or send an e-mail to luis.fernando.salgueiro@upc.edu